Evidence map›Paper›PMID 32493225›Full record

ArticleBMC medical research methodology2020

No one accelerometer-based physical activity data collection protocol can fit all research questions.

Patrick Bergman, Maria Hagströmer

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in BMC medical research methodology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06169020 (Design of an Intelligent Wearable to Assess Physical Activity and Health Related Outcomes - the DIWAH Study), which is not on this map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.0field-weighted citation impact, top 25% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT06169020 naenrolling by invitationnot on this mapstarted 2023, after this paper: background citation

Design of an Intelligent Wearable to Assess Physical Activity and Health Related Outcomes - the DIWAH Study

TypeinterventionalSponsorLinnaeus UniversityRan2023 to 2027Enrolled50ConditionsHealth PromotionArmsResting and maximal oxygen consumtion, Free living energy expenditure
3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 12 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 2 institutions in 1 country.

Patrick BergmanDepartment of medicine and optometry, eHealth Institute, Linnaeus University, 39182, Kalmar, Sweden. patrick.bergman@lnu.se.ORCID 0000-0003-4934-8684
Maria HagströmerKarolinska Institutet, Department of Neurobiology, Care Sciences and Society, Division of Physiotherapy, Alfred Nobels Allé 23, 141 83, Huddinge, Sweden.
Karolinska University Hospital · SELinnaeus University · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMeasuring physical activity and sedentary behavior accurately remains a challenge. When describing the uncertainty of mean values or when making group comparisons, minimising Standard Error of the Mean (SEM) is important. The sample size and the number of repeated observations within each subject influence the size of the SEM. In this study we have investigated how different combinations of sample sizes and repeated observations influence the magnitude of the SEM.

methodsA convenience sample were asked to wear an accelerometer for 28 consecutive days. Based on the within and between subject variances the SEM for the different combinations of sample sizes and number of monitored days was calculated.

resultsFifty subjects (67% women, mean ± SD age 41 ± 19 years) were included. The analyses showed, independent of which intensity level of physical activity or how measurement protocol was designed, that the largest reductions in SEM was seen as the sample size were increased. The same magnitude in reductions to SEM was not seen for increasing the number of repeated measurement days within each subject.

conclusionThe most effective way of reducing the SEM is to have a large sample size rather than a long observation period within each individual. Even though the importance of reducing the SEM to increase the power of detecting differences between groups is well-known it is seldom considered when developing appropriate protocols for accelerometer based research. Therefore the results presented herein serves to highlight this fact and have the potential to stimulate debate and challenge current best practice recommendations of accelerometer based physical activity research.

Indexed as

ExerciseSedentary BehaviorAccelerometryAdultData CollectionFemaleHumansMaleMiddle AgedSample SizeYoung Adult

Identifiers

PMID32493225
PMCPMC7271555
OpenAlexW3030285260

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.